Sunil Kumar Khare | Green Technology | Outstanding Scientist Award

Outstanding Scientist Award

Sunil Kumar Khare
University of Petroleum and Energy Studies, India

Sunil Kumar Khare
Affiliation University of Petroleum and Energy Studies
Country India
Scopus ID 26324209600
Documents 18
Citations 214
h-index 7
Subject Area Green Technology
Event Technology Scientists Awards
ORCID 0000-0001-5041-3012

Sunil Kumar Khare is a researcher affiliated with the University of Petroleum and Energy Studies in India whose scholarly profile encompasses green technology and data-driven engineering research. His documented work includes applications of analytics, regression modelling, pipeline network optimization, and geochemical interpretation, demonstrating an interdisciplinary orientation toward technology-enabled scientific problem solving. [1] [2] [3]

Abstract

Sunil Kumar Khare is a researcher at the University of Petroleum and Energy Studies, India, working within the broad domain of Green Technology. His scholarly record includes research involving data analytics, regression modelling, engineering optimization, and geochemical analysis. His publications demonstrate applications of computational methods to energy and geological problems, including geothermal drilling, pipeline configuration, and igneous-province characterization. These studies illustrate an interdisciplinary research profile connecting analytical techniques with practical engineering and environmental contexts. His documented scholarly output and citation record provide evidence of sustained research engagement and academic visibility. [1] [2] [3]

Keywords

Green Technology; Data Analytics; Regression Modelling; Geothermal Wells; Drilling Engineering; Pipeline Network Optimization; Sensitivity Analysis; Geochemistry; Petrogenetics; Igneous Provinces; Energy Technology; Engineering Analytics.

Introduction

Green Technology increasingly depends on analytical methods capable of improving resource efficiency, engineering decisions, and environmental understanding. Khare’s research reflects this interdisciplinary direction through studies applying data analytics to geothermal drilling, optimization to pipeline networks, and analytical methods to geological characterization, connecting computational approaches with energy and Earth-science applications. [1] [2] [3]

Research Profile

Khare’s research profile combines engineering analytics, optimization, and geoscientific investigation. His documented publications address prediction of drilling performance, multi-product pipeline configuration, and data-supported interpretation of geochemical and petrogenetic characteristics. Together, these themes indicate a research orientation toward quantitative methods that support complex energy, infrastructure, and geological systems across applied scientific contexts. [1] [2] [3]

Research Contributions

The documented research contributes analytical perspectives to energy and geological engineering problems. Regression modelling is applied to geothermal drilling-rate prediction, optimization frameworks examine pipeline configuration and objective-function sensitivity, while data analytics supports geochemical and petrogenetic interpretation. These contributions demonstrate the practical use of quantitative approaches for complex, multidisciplinary technological investigations. [1] [2] [3]

Publications

Khare’s documented publications cover three complementary areas: predictive analytics for geothermal drilling, optimization of multi-product pipeline networks, and data analytics for geochemical and petrogenetic investigation. These works illustrate the application of quantitative and computational techniques to engineering and Earth-science questions, with relevance to energy systems and technology-oriented research. [1] [2] [3]

Research Impact

The research demonstrates potential practical relevance across geothermal energy, pipeline infrastructure, and geological interpretation. Predictive modelling can support drilling analysis, optimization can inform network configuration decisions, and geochemical analytics can strengthen interpretation of complex geological datasets. The combined portfolio reflects technology-oriented research addressing diverse analytical challenges within energy-related domains. [1] [2] [3]

Award Suitability

Khare’s documented research aligns with the broad objectives of scientific recognition in technology-oriented disciplines. His work combines analytical modelling, engineering optimization, and geoscientific data analysis, while addressing energy and infrastructure applications. The breadth of these themes provides a reasonable basis for consideration under an Outstanding Scientist Award focused on applied technological research. [1] [2] [3]

Conclusion

Sunil Kumar Khare presents a multidisciplinary research profile spanning green technology, energy engineering, optimization, predictive analytics, and geoscience. His documented publications demonstrate the application of quantitative approaches to practical scientific problems. The combination of engineering and Earth-science research provides a substantive foundation for consideration for technology-focused scientific recognition. [1] [2] [3]

References

  1. Khare, S. K., et al. (2025). Data analytics and regression modelling for drilling rate of penetration prediction of geothermal wells. In Advances in Energy and Environmental Engineering. Springer.
    https://doi.org/10.1007/978-981-96-3667-9_11
  2. Khare, S. K., et al. (2024). Optimizing multi-product pipeline network configuration design: A comprehensive framework with objective function sensitivity analysis. Scopus. Publication record: 85184306294.
    https://www.scopus.com/pages/publications/85184306294
  3. Khare, S. K., et al. (2024). Data analytics for geochemical and petrogenetic study of an igneous province: A case study on Andean andesite, South America. Journal of Earth System Science.
    https://doi.org/10.1007/s12040-024-02399-9
  4. Elsevier. (n.d.). Scopus author details: Sunil Kumar Khare, Author ID 26324209600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=26324209600
  5. ORCID. (n.d.). Sunil Kumar Khare: ORCID record. ORCID.
    https://orcid.org/0000-0001-5041-3012

Zehra Gulten Yalcın | Renewable Energy | Best Researcher Award

Best Researcher Award

Zehra Gulten Yalcın — Çankırı Karatekin University, Turkey

Zehra Gulten Yalcın
Affiliation Çankırı Karatekin University
Country Turkey
Scopus ID 6603311969
Documents 8
Citations 60
h-index 5
Subject Area Renewable Energy
Event Technology Scientists Awards
ORCID 0000-0001-5460-289X

Zehra Gülten Yalçın is a researcher affiliated with Çankırı Karatekin University whose scholarly work addresses sustainable engineering, renewable-energy-related processes, industrial waste valorization, corrosion inhibition, polymer composites, and anaerobic digestion. Her recent publications demonstrate an interdisciplinary approach combining experimental investigation, materials characterization, optimization, and data-driven analysis in applied engineering research. [1] [2] [3]

Abstract

Zehra Gülten Yalçın is an engineering researcher at Çankırı Karatekin University whose recent scholarly activities connect sustainable materials, waste utilization, corrosion control, anaerobic digestion, and renewable-energy-oriented engineering. Her publications examine industrial waste in polymer composites, environmentally compatible corrosion inhibition, and optimization of biogas production using experimental and response-surface methodologies. These studies demonstrate an applied research orientation focused on converting industrial and biological waste streams into useful engineering outcomes while improving process performance and sustainability. Her work also incorporates characterization, optimization, and analytical methods to investigate material behavior and energy-related processes. [1] [2] [3]

Keywords

  • Renewable Energy
  • Sustainable Engineering
  • Industrial Waste Valorization
  • Polymer Composites
  • Corrosion Inhibition
  • Anaerobic Digestion
  • Biogas Production
  • Process Optimization

Introduction

Zehra Gülten Yalçın’s research is situated within sustainable chemical and environmental engineering, with particular relevance to waste utilization and energy-related processes. Her recent studies investigate polymer composites containing industrial waste, natural corrosion inhibitors, and anaerobic digestion systems, reflecting practical approaches to resource efficiency, materials performance, and renewable-energy development. [1] [2] [3]

Research Profile

Yalçın’s research profile combines materials engineering, environmental processes, and sustainable energy applications. Her publications indicate experience with experimental methods, material characterization, process optimization, and quantitative analysis. The research addresses practical engineering problems involving industrial waste, corrosion protection, polymeric materials, and biological waste conversion, providing an interdisciplinary foundation for continued work in renewable and sustainable technologies. [1] [2] [3]

Research Contributions

Her contributions include investigation of industrial waste as functional fillers in polyurethane composites, evaluation of Turkish coffee extract as an environmentally oriented corrosion inhibitor, and optimization of anaerobic digestion for biogas generation. Together, these studies connect resource recovery, materials performance, environmental protection, and renewable-energy production through experimentally grounded engineering approaches and quantitative process analysis. [1] [2] [3]

Publications

Yalçın’s recent publication record includes studies spanning sustainable polymer composites, corrosion science, and anaerobic digestion. A 2026 article examined industrial waste incorporation into polyurethane composites and associated mechanical and thermal properties, while a 2025 study investigated Turkish coffee extract for corrosion inhibition. Another 2025 publication examined biogas optimization using response surface methodology. [1] [2] [3]

Research Impact

The practical orientation of Yalçın’s research provides potential value for sustainable manufacturing, environmental protection, and renewable-energy development. Her studies address waste-derived materials, greener corrosion-control strategies, and biological waste conversion into biogas. These themes align with broader efforts to improve resource efficiency and develop engineering solutions that reduce environmental burdens while supporting useful material and energy recovery. [1] [2] [3]

Award Suitability

Yalçın’s documented research activity is relevant to recognition in sustainable and renewable-energy-oriented research because her work integrates waste valorization, environmental engineering, materials development, and biogas production. Her publication portfolio demonstrates a coherent interest in practical sustainability challenges, supported by experimental investigation and analytical methods. These characteristics provide a reasonable academic basis for consideration for the Best Researcher Award. [1] [2] [3]

Conclusion

Zehra Gülten Yalçın’s recent scholarship demonstrates interdisciplinary engagement with sustainable engineering problems involving materials, waste, corrosion, and renewable-energy processes. Her research combines experimental studies with optimization and analytical approaches, contributing to applied knowledge in environmentally relevant engineering fields. The breadth and practical orientation of these publications support continued development within sustainable technology research. [1] [2] [3]

References

  1. Dağ, M., Aydoğmuş, E., Yalçın, Z. G., & Arslanoğlu, H. (2026). Valorization of industrial waste in polymer composites: Enhancing mechanical and thermal properties for insulation applications using machine learning analysis. Polymer Engineering & Science, 66(1), 470–486.
    https://doi.org/10.1002/pen.70230
  2. Hussein, M. Y., Yalçın, Z. G., Yaqoob, G. B., & Dağ, M. (2025). Investigation of the corrosion-inhibition effect of Turkish coffee extract on L-80 carbon steel in 15% HCl: Thermodynamic and surface analyses. Petroleum Science and Technology, 43(25), 3757–3795.
    https://doi.org/10.1080/10916466.2025.2536474
  3. Günay, K., & Yalçın, Z. G. (2025). Maximizing biogas yield in anaerobic digestion: A response surface methodology approach. Black Sea Journal of Engineering and Science, 8(4), 1103–1110.
    https://doi.org/10.34248/bsengineering.1683991
  4. Elsevier. (n.d.). Scopus author details: Zehra Gülten Yalçın, Author ID 6603311969. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=6603311969
  5. ORCID. (n.d.). Zehra Gülten Yalçın: ORCID record 0000-0001-5460-289X. ORCID.
    https://orcid.org/0000-0001-5460-289X

Wentao Shang | Green Technology | Best Researcher Award

Best Researcher Award

Wentao Shang
Affiliation Jinan University
Country China
Scopus ID 57604364900
Documents 34
Citations 812
h-index 15
Subject Area Green Technology
Event Technology Scientists Awards
ORCID 0000-0002-5168-7696

Wentao Shang is affiliated with Jinan University, China, and works across membrane science, separation technologies, computational prediction, imaging, and advanced materials. His recent scholarly record includes research on membrane distillation, nanofiltration fouling prediction, and supramolecular materials, providing a multidisciplinary basis for consideration within the field of green technology. [1] [2] [3]

Abstract

Wentao Shang is a researcher at Jinan University whose documented work connects membrane science, green technology, computational modeling, imaging, and advanced materials. His recent publications examine surface patterning for membrane distillation, multimodal convolutional neural networks for dynamic nanofiltration fouling prediction, and solution-sheared supramolecular oligomers with improved thermal-resistant adhesion. These studies demonstrate an interdisciplinary approach combining materials engineering, separation processes, experimental characterization, and data-driven analysis. With 34 documented publications, 812 citations, and an h-index of 15, his profile indicates sustained scholarly activity and measurable research visibility. The breadth and environmental relevance of these themes support consideration for a Best Researcher Award.

Keywords

Keywords: Green Technology, Membrane Distillation, Nanofiltration, Membrane Fouling, Optical Coherence Tomography, Convolutional Neural Networks, Surface Patterning, Advanced Materials, Supramolecular Oligomers, Sustainable Engineering.

Introduction

Wentao Shang’s research profile at Jinan University reflects an interdisciplinary focus connecting membrane processes, nanofiltration, imaging-based analysis, advanced materials, and sustainable engineering. His recent publications address membrane distillation, fouling prediction, and thermally resistant supramolecular materials, indicating a research trajectory relevant to emerging green technology and resource-efficient engineering. [1] [2] [3]

Research Profile

Shang is associated with research spanning membrane science, separation technologies, computational prediction, and functional materials. His publication record includes studies using surface patterning to improve membrane distillation and multimodal convolutional neural networks to model nanofiltration fouling. These themes connect experimental characterization, materials engineering, and data-driven methods for environmental applications. [1] [2]

Research Contributions

Shang’s contributions can be viewed through three complementary areas: engineering membrane surfaces for improved separation performance, applying in-situ optical coherence tomography and multimodal neural networks to characterize fouling dynamics, and investigating supramolecular materials with enhanced thermal and adhesive properties. Together, these studies demonstrate integration of experimental methods, computational analysis, and materials design. [1] [2] [3]

Publications

The documented publications associated with Shang include a 2026 review of surface patterning in membrane distillation, a 2026 Desalination article on multimodal convolutional neural networks for nanofiltration fouling prediction, and a Nature Communications study on solution-sheared supramolecular oligomers. The works collectively cover membrane engineering, machine learning, imaging, adhesion, and advanced materials. [1] [2] [3]

Research Impact

The research has potential relevance to green technology through improved membrane efficiency, fouling management, and durable functional materials. Surface-engineered membranes may support cleaner separation processes, while predictive imaging models can improve understanding of fouling development. Work on thermally resistant adhesives further broadens the profile toward resource-conscious and performance-oriented materials engineering. [1] [2] [3]

Award Suitability

The Best Researcher Award profile is supported by a combination of publication activity, citation indicators, interdisciplinary research themes, and alignment with green technology. The reported record of 34 documents, 812 citations, and an h-index of 15 provides quantitative evidence of scholarly visibility, while recent publications demonstrate continuing research activity. [1] [2] [3]

Conclusion

Wentao Shang presents a research profile combining membrane technology, computational modeling, imaging, and advanced materials. His recent work addresses practical challenges in separation efficiency, fouling prediction, and material durability. The combination of documented scholarly output and green-technology relevance provides a reasonable academic basis for consideration under the Best Researcher Award. [1] [2] [3]

References

  1. Zhang, C., Lin, Y., Lu, G., Yuan, B., Chen, P., Farid, M. U., Lee, V. P. H., Shang, W., Li, W., & An, A. K. (2026). Surface patterning in membrane distillation: Fabrication, mechanism, and performance enhancement. Separation and Purification Technology, 394(Part 3), Article 137561.
    https://www.sciencedirect.com/science/article/abs/pii/S1383586626008270
  2. Shang, W., Zeng, Y., Xiao, F., Wu, M., Wang, Y., Yang, Z., He, J., & Sun, F. (2026). A multimodal convolutional neural network trained by in-situ OCT characterization for dynamic structural prediction of nanofiltration fouling. Desalination, 639, Article 120676.
    https://www.sciencedirect.com/science/article/pii/S0011916426008325
  3. Lu, G., Ma, R., Zhao, Y., Wang, D., Shang, W., Chen, H., Khan, S. A., Li, M., & Saiz, E. (2025). Solution-sheared supramolecular oligomers with enhanced thermal resistance in interfacial adhesion and bulk cohesion. Nature Communications, 16, 7754.
    https://www.nature.com/articles/s41467-025-63123-9
  4. Elsevier. (n.d.). Scopus author details: Wentao Shang, Author ID 57604364900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57604364900
  5. ORCID. (n.d.). Wentao Shang, ORCID 0000-0002-5168-7696. ORCID.
    https://orcid.org/0000-0002-5168-7696

Chengyu Liang | Renewable Energy | Innovative Research Award

Innovative Research Award

Chengyu Liang
Lanzhou University of Technology, China
               Chengyu Liang
Affiliation Lanzhou University of Technology
Country China
Scopus ID 57469530600
Documents 3
Citations 22
h-index 2
Subject Area Renewable Energy
Event Technology Scientists Awards

Chengyu Liang is a researcher affiliated with Lanzhou University of Technology whose scholarly work focuses on renewable energy technologies and intelligent condition assessment of engineering systems. The available Scopus profile indicates a growing publication record with measurable citation impact, reflecting sustained academic contributions to reliability analysis, predictive maintenance, and energy-related engineering research.[1]

Abstract

Chengyu Liang has contributed to engineering research involving renewable energy applications, machinery health monitoring, degradation assessment, and intelligent predictive models. Current scholarly records demonstrate emerging influence through peer-reviewed publications indexed in Scopus and measurable citation performance. Research activities emphasize adaptive state-space modelling, prediction error correction, and reliability evaluation for mechanical systems supporting sustainable engineering development. These studies combine mathematical modelling with practical engineering applications to improve equipment performance, operational efficiency, maintenance planning, and long-term system reliability. The available publication record reflects continuing academic development and meaningful contributions within renewable energy and engineering research communities.[1][2]

Keywords

Renewable Energy, Mechanical Systems, Performance Degradation, State-Space Model, Predictive Maintenance, Reliability Engineering, Adaptive Modeling, Engineering Diagnostics.

Introduction

Chengyu Liang conducts engineering research centered on renewable energy and intelligent mechanical system analysis. Published studies investigate advanced degradation assessment methodologies using adaptive mathematical models that improve equipment reliability, operational efficiency, and predictive maintenance while supporting sustainable engineering practices and modern industrial applications.[2]

Research Profile

According to publicly available Scopus records, Chengyu Liang has authored three indexed publications that have received twenty-two citations with an h-index of two. The research portfolio reflects specialization in engineering diagnostics, renewable energy technologies, reliability assessment, and predictive analytical modelling.[1]

Research Contributions

Research contributions include developing adaptive state-space approaches for evaluating mechanical performance degradation using prediction error correction techniques. These methods enhance condition monitoring accuracy, facilitate maintenance decision-making, and improve reliability evaluation across engineering systems supporting renewable energy and industrial sustainability objectives.[2]

Publications

The publication record includes peer-reviewed research focused on degradation assessment methodologies for mechanical systems. A representative article presents a dual adaptive drift coefficient state-space model integrated with autocorrelation prediction error correction, demonstrating practical applications in engineering reliability and intelligent equipment monitoring.[2]

Research Impact

Citation metrics and indexed publications indicate growing academic recognition within engineering research. The integration of predictive modelling with mechanical system assessment contributes valuable knowledge supporting efficient maintenance strategies, equipment longevity, and sustainable industrial operations in renewable energy and manufacturing environments.[1]

Award Suitability

The Innovative Research Award recognizes researchers demonstrating originality, measurable scholarly contributions, and practical engineering significance. Chengyu Liang’s research on adaptive degradation assessment and predictive maintenance aligns with these principles by advancing analytical methodologies applicable to renewable energy and engineering reliability studies.[2]

Conclusion

Chengyu Liang has established an emerging research profile through focused engineering investigations addressing renewable energy, reliability assessment, and intelligent predictive modelling. Available scholarly evidence indicates continuing academic development, making this body of work an appropriate example of innovative engineering research recognized through academic award evaluation.[1]

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Chengyu Liang, Author ID 57469530600. Scopus.
    https://www.scopus.com/pages/authors/57469530600
  2. Liang, C., et al. (2025). Performance degradation assessment of mechanical system based on dual adaptive drift coefficient state-space model with autocorrelation prediction error correction. Mechanical Systems and Signal Processing. Elsevier.
    https://www.sciencedirect.com/science/article/abs/pii/S0888327025015055
  3. Technology Scientists Awards. (n.d.). Technology Scientists Awards official website.
    https://technologyscientists.com/

Marina Gravit | Sustainable Tech | Women Researcher Award

Women Researcher Award

Marina Gravit
Peter the Great St.Petersburg Polytechnic University

                             Marina Gravit
Affiliation Peter the Great St.Petersburg Polytechnic University
Country Russia
Scopus ID 56826013600
Documents 104
Citations 780
h-index 15
Subject Area Sustainable Tech
Event Technology Scientists Awards
ORCID 0000-0003-1071-427X

Marina Gravit is a researcher affiliated with Peter the Great St.Petersburg Polytechnic University whose scholarly work focuses on fire safety engineering, sustainable construction materials, structural fire resistance, and passive fire protection technologies. Her research contributes to the advancement of resilient infrastructure and evidence-based approaches for improving building safety under severe fire conditions.[1]

Abstract

This article presents an overview of Marina Gravit’s academic profile, emphasizing her contributions to fire resistance engineering, passive fire protection systems, and sustainable construction technologies. Her publications address critical challenges in structural safety, predictive fire resistance assessment, and the application of advanced protective materials for industrial and civil infrastructure.[1][2]

Keywords

Fire Resistance, Structural Engineering, Passive Fire Protection, Sustainable Construction, Fire Safety Materials, Hydrocarbon Fire Conditions, Steel Structures, Building Safety, Fire Protection Engineering, Sustainable Technology.

Introduction

Marina Gravit’s research addresses contemporary challenges in fire safety engineering through studies of fire-resistant materials, structural performance, and protective technologies. Her work integrates sustainability and engineering reliability, supporting safer infrastructure development while advancing scientific understanding of fire behavior and protection strategies in modern construction environments.[1]

Research Profile

As a scholar in fire safety and construction engineering, Marina Gravit has developed a substantial publication record focused on building resilience, fire protection materials, and structural safety assessment. Her interdisciplinary approach combines engineering analysis, material science, and sustainability principles to address practical and scientific challenges.[1][3]

Research Contributions

Her contributions include investigations of passive fire protection systems, bibliometric analyses of fire-resistant construction technologies, and predictive methodologies for assessing steel structures under hydrocarbon fire exposure. These studies support evidence-based engineering decisions and contribute to enhanced safety standards in industrial and commercial infrastructure.[2][3]

Publications

Notable publications examine fire resistance in building structures, passive protection materials for steel systems exposed to jet fires, and forecasting models for structural performance during hydrocarbon fire scenarios. These works provide valuable insights into fire engineering design, safety optimization, and protective material evaluation.[1][2][3]

Research Impact

The impact of Marina Gravit’s research is reflected in scholarly citations, practical relevance to fire safety engineering, and contributions to safer structural design practices. Her studies support researchers, engineers, and policymakers seeking improved methodologies for fire resistance assessment and infrastructure protection.[1][3]

Award Suitability

Marina Gravit demonstrates strong suitability for the Women Researcher Award through her sustained scholarly productivity, international research visibility, and contributions to sustainable technology and fire safety engineering. Her work addresses critical societal challenges while advancing knowledge relevant to resilient and sustainable built environments.[1][2]

Conclusion

Marina Gravit’s academic achievements illustrate a commitment to advancing fire safety science, sustainable construction technologies, and structural resilience. Through influential research and practical engineering applications, she has contributed valuable knowledge supporting safer infrastructure and ongoing innovation within the field of sustainable technology.[1][3]

References

  1. Gravit, M., et al. (2025). Fire Resistance of Building Structures and Fire Protection Materials: Bibliometric Analysis. Fire, 8(1), 10.
    https://www.mdpi.com/2571-6255/8/1/10
  2. Gravit, M., et al. (2024). Impact of Jet Fires on Steel Structures: Application of Passive Fire Protection Materials. Fire, 7(8), 281.
    https://www.mdpi.com/2571-6255/7/8/281/review_report
  3. Gravit, M., et al. (2024). Oil and Gas Structures: Forecasting the Fire Resistance of Steel Structures with Fire Protection under Hydrocarbon Fire Conditions. Fire, 7(6), 173.
    https://www.mdpi.com/2571-6255/7/6/173
  4. Elsevier. (n.d.). Scopus author details: Marina Gravit, Author ID 56826013600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56826013600
  5. ORCID. (n.d.). Marina Gravit ORCID Record.
    https://orcid.org/0000-0003-1071-427X

Bellel Nadir | Renewable Energy | Best Researcher Award

Prof. Bellel Nadir | Renewable Energy | Best Researcher Award

Dean | University of Constantine 1 | Algeria

Prof. Bellel Nadir is a multidisciplinary researcher specializing in sustainable materials, thermal–fluid systems, and energy-efficient engineering solutions. With a portfolio of 20 scientific publications, 126 citations and 7 h-index, his work advances bio-based construction materials and solar-driven thermal technologies. Notable contributions include the development of lightweight bio-concretes using agricultural waste and optimized CFD-based designs for solar concentrator systems. His research is strengthened by collaborations with more than 20 international co-authors, reflecting broad academic engagement. Bellel’s work supports global sustainability goals by promoting renewable-energy applications, valorizing biomass residues, and improving eco-friendly construction practices, thereby offering measurable environmental and societal benefits.

Citation Metrics (Scopus)

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